Metabolomic and Gene Expression Profiles Exhibit Modular Genetic and Dietary Structure Linking Metabolic Syndrome Phenotypes in Drosophila

Author:

Williams Stephanie1,Dew-Budd Kelly12,Davis Kristen1,Anderson Julie1,Bishop Ruth2,Freeman Kenda1,Davis Dana2,Bray Katherine2,Perkins Lauren2,Hubickey Joana2,Reed Laura K112

Affiliation:

1. Department of Genetics, North Carolina State University, Raleigh, North Carolina 27695

2. Department of Biological Sciences, University of Alabama, Tuscaloosa, Alabama 35487

Abstract

Abstract Genetic and environmental factors influence complex disease in humans, such as metabolic syndrome, and Drosophila melanogaster serves as an excellent model in which to test these factors experimentally. Here we explore the modularity of endophenotypes with an in-depth reanalysis of a previous study by Reed et al. (2014), where we raised 20 wild-type genetic lines of Drosophila larvae on four diets and measured gross phenotypes of body weight, total sugar, and total triglycerides, as well as the endophenotypes of metabolomic and whole-genome expression profiles. We then perform new gene expression experiments to test for conservation of phenotype-expression correlations across different diets and populations. We find that transcript levels correlated with gross phenotypes were enriched for puparial adhesion, metamorphosis, and central energy metabolism functions. The specific metabolites L-DOPA and N-arachidonoyl dopamine make physiological links between the gross phenotypes across diets, whereas leucine and isoleucine thus exhibit genotype-by-diet interactions. Between diets, we find low conservation of the endophenotypes that correlate with the gross phenotypes. Through the follow-up expression study, we found that transcript-trait correlations are well conserved across populations raised on a familiar diet, but on a novel diet, the transcript-trait correlations are no longer conserved. Thus, physiological canalization of metabolic phenotypes breaks down in a novel environment exposing cryptic variation. We cannot predict the physiological basis of disease in a perturbing environment from profiles observed in the ancestral environment. This study demonstrates that variation for disease traits within a population is acquired through a multitude of physiological mechanisms, some of which transcend genetic and environmental influences, and others that are specific to an individual’s genetic and environmental context.

Publisher

Oxford University Press (OUP)

Subject

Genetics (clinical),Genetics,Molecular Biology

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